How to Interpret Truth From Facts

When is a fact true? This is a major question we’re asking given the pre/post-election. Sometimes, the answer isn’t a simple yes it’s true or no it’s not true. Sometimes the caveat “it depends…” provides critical insight into the context, constraints, veracity and therefore, applicability of the fact.

Let’s take 2 seemingly contradictory facts we’ve heard this past year:

• Violent crime is up
• Violent crime is down

According to the FBI and other studies, overall violent crime in the USA is at historic lows over the past 30, 10 and 5 years.  Yet, when you examine the data in the same studies, it becomes clear both statements above are true:

• There is a 5.5% rise is violent crime from 2015 to 2016 with half of that coming from LA and Chicago and yet, the overall rate is still at the “bottom of the nation’s 30-year downward trend.”
• Chicago accounts for almost half the increase in murders from 2015 to 2016 with decreasing murder rates in Baltimore and Washington D.C. and New York as one of safest big cities.

Bottom line? Both facts are true.  What you do with those facts depends on the questions you ask about those facts. What you ask with the subsequent iteration of answers and questions, is critical for making wise informed decisions.  So try asking:

• What is the timeframe?
• Are there outliers?
• What did/didn’t these facts (and underlying data) take into account (what’s missing)?
• What do these facts assume?
• How long will these facts be true?
• Who did the study and who paid for it?
• What other questions arise from this fact?
• What would it mean if this wasn't true? Who would benefit or be harmed?
• etc.....

The ability to interpret truth from facts is a critical skill for success - in business and in life.  So starting today, or okay, tomorrow, ask questions when you're presented with facts - sales, recruiting, efficiency, inventory, market trends, anything - just start and see what you learn!

Death by Data

Data isn’t important in decision-making. What? Shocking! Then why aren’t we shocked when someone says that all decisions must be totally data driven? Perhaps it depends what we mean by data, which is usually something quantitative. 

We need to get out into the world and gather data by watching, observing, listening, asking – qualitative data. We don’t live in a binary world – it’s not either-or, it’s and-both.  We need quantitative and qualitative data. We need to consider both equally valid forms of data.  After all, as the sociologist William Bruce Cameron said (guess Einstein didn’t *),

“Not everything that can be counted counts. Not everything that counts can be counted.”

Quantitative data needs to be part of the equation, part, not all.  More and more I see companies defining “data” as purely quantitative, dismissing or minimizing, at their peril, the importance of the qualitative.  Quantitative data can tell us a lot.  It an also tell us little.  Quantitative data has limitations – as does everything. These limitations are because the data usually is…

• About existing “stuff”. It tells us about our current features, functions, customers and markets.  It tells us what customers are [stuck] using now, not what they really want.  It doesn’t tell us what our “stuff” could become or what new customers, markets and applications are out there;
• Based in the present or the past.  We don’t have much ‘future’ data: what will, could, should or might be and what we could do to make that happen;
• A glimpse in time.  It can be a year, five years, ten years, but it’s always piece of the bigger picture;At the Edge (Pemaquid Point, ME)
• About the what, where, why and maybe even how, but rarely the why. Data usually doesn’t tell us much about fringe factors or trends that impact it.  It’s hard to have data show us the subtle societal, cultural, behavioral “whys” of influence;
• Used to make things more efficient instead of more effective. Yes, efficiency (or optimization to be more eloquent) still rules for most of business today.  Data helps us figure out to eliminate unnecessary steps, improve productivity, reduce costs, etc.  Data doesn’t necessarily tell us why things need to be improved in the first place or new, different ways of doing, period.

As I like to tell my engineering students, most of today’s wicked problems aren’t optimization problems; they are system and design problems.  Think of the remote controls on your den table! Optimization issues are a symptom, not a root cause.  Data doesn’t necessarily tell us how to make the problem go away because it doesn’t tell us why the problem is there in the first place.  We have to actually get out of the office and look at how the problem is being addressed, not addressed, or not well enough by human beings.  We need to see how things are organized, structured, laid out, used, not used and under what conditions, circumstances and contexts. 

Data can tell us a whole lot about how our sites and stores and companies are working or not working, but data can’t necessarily tell us the whys – why it is or isn’t working, or working well enough. Without getting out and observing reality first-hand with all our five senses, we risk optimizing our organization into extinction. 

* http://quoteinvestigator.com/2010/05/26/everything-counts-einstein/

Don’t Let Probable Trump Possible

I don’t buy lottery tickets. Perhaps I should. When it’s the huge MegaMillions^® I think about it, but I don’t.  Why? Because, while it is definitely Possible that I could win, it’s not highly Probable.

We interchangeably use Possible and Probable or view them as ‘either/or’ options instead of ‘and/both’. Let’ break down this artificial distinction!  One way I try to get clients, entrepreneurs, and students to look at the world differently is by challenging them to look at what is Possible AND Probable, no matter how Probable it is.  Unless we are defying the laws of physics, more things are Possible than we think. They may not be highly probable, but that’s a different issue.

Possible means “able to be done, within the power or capacity of someone or something.” It comes from the Latin possibilis (that can be done) and from posse (be able).   The meaning of the word has nothing to do with likelihood… probability.  Possible has to do with whether something CAN be done, happen or be true, not IF it will be. Possible doesn’t address likelihood (probability) or difficulty. 

Probable means [how] “likely something is to be the case or to happen”.  It comes from the Old French probable (provable, demonstrable) and Latin probabilis (worthy of approval; provable; credible; testable).  The meaning of the word may assume a level of possibility (e.g., if it’s impossible, it’s not probable), but it does not define what is possible.

Possible is usually based on the laws of science – physics, chemistry, and biology.  It’s pretty hard to break the law of gravity while on earth.  But, is it possible for a man to lift an elephant? It is actually possible depending on the size of the man, the size of the elephant, angles, centers of gravity, etc.  Does what is possible change over time or is it our knowledge of what is possible that changes as we make discoveries and advances in technology and science? Both?

Probable is a bit trickier.  Improbable things happen all the time.  Cancers suddenly disappear without a plausible explanation… it was always possible, just not very probable.  I win the lottery – it is possible, just not very probable (of course buying a ticket helps). You’d be surprised how often our definition of what is probable has little to do with real statistical data.  You’d also be surprised at how we tend to shy away from things that are not very probable.  We also tend to define what is probable based upon our own worldview, perceptions and experiences.   Think of the Gambler’s Fallacy - if something happens a lot, we start thinking it’s going to happen a lot (e.g., I flip a coin 5 times and it’s always heads so I think the next time has to be tails, but it’s still a 50/50 chance).  Dan Ariely’s TED talk shows our subjectivity on probability.

This summer, as you work on existing and new projects, start asking if potential solutions are Possible AND Probable.  Then ask why doesn’t something seem probable? Is it your worldview? Biases? Experiences? What would it take to be more probable?  This may require you start rushing to discover instead of solve and it may open up new Possibilities!  Give it a try.